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Quantitative Reasoning

Welcome to Lehman College's Quantitative Reasoning (QR) program. Our program is committed to infusing numerical literacy across all curriculums. Our program is based on the belief that QR is essential in teaching students to think critically and apply basic mathematics skills to interpret data, draw conclusions, and solve problems within a disciplinary and interdisciplinary context. Quantitative reasoning skills are among the intellectual and practical skills considered essential for LEAP (Liberal Education and America's Promise) and are among the Institutional Learning goals for the "Characteristics of a Lehman Graduate."

Much of the information accessed through the internet or other forms of media is quantitative in nature, and students must be equipped with the basic skills to effectively analyze this information as they make important decisions in their everyday lives. QR skills are also necessary in business, education, health and government settings, where many of our students will be working. While most students associate QR with basic mathematic courses, we are committed to the notion that QR skills encompass a wider set of skills grounded in the ability to understand and interpret numerical information in both theoretical and applied settings.

About Quantitative Reasoning

What is QR? Most simply, QR skills refer to the ability to reason quantitatively and to model and solve problems with quantitative (or numerical) methods. While QR is inextricably tied to mathematics, QR skills can be applied more broadly to daily tasks such as calculating interest rates on a consumer credit card, understanding polling results, or estimating one's risk of contracting the Ebola virus by holding on to a subway pole. At the undergraduate level, QR skills also refer to students' ability to apply data and numerical evidence to theoretical questions. According to the AAC&U, quantitative reasoning (QR) is, "the application of basic math skills, such as algebra, to the analysis and interpretation of real-world quantitative information in the context of a discipline or an interdisciplinary problem to draw conclusions that are relevant to students in the daily lives."

The difference between mathematics and QR/numeracy: "Numeracy is not the same as mathematics, nor is it an alternative to mathematics…today's students need both mathematics and numeracy."

Mathematics Numeracy/QR
Power of abstraction Power of practicality
Same context dependency Heavy context dependency
Organized by categories inherited from the past Focuses on the way knowledge is used in the information age
Discipline specific Interdisciplinary
Encountered mostly in school Used in real life and in school

QR refers to a more general set of skills that allow students to analyze and integrate numerical thinking into a range of contexts. QR skills are encountered on a daily basis, and can refer to one's ability to understanding polling data, or make sense of a graph. An English student, for example, can engage in quantitative reasoning when counting the number of times a certain word or grammatical structure is used in a text.

Why is infusing QR across the disciplines important? While many of the liberal arts are not traditionally associated with QR, the AAC&U stresses that QR is "located at the intersection of critical thinking, basic mathematics skills, and the disciplines or real-world contexts for learning." Importantly, in order to truly assess QR competency, students must be able to identify and apply quantitative relationships in a range of contexts, even ones that are not usually associated with numeracy. It is easy to spot QR across a wide range of disciplines, including: public health (e.g. assessing the association between vaccines and autism), political science (e.g. making judgments based on political polling), dietetics (e.g. interpreting nutritional facts and labels) and even literature and the arts. However, according to the AAC&U, a 2003 survey revealed that only 13 percent of American adults are proficient in quantitative literacy, while 22 percent are below basic level.

Resources for Faculty


The AAC&U recommends 6 QR skills to be assessed in students' work:

Skill Definition
Interpretation Explain information presented in mathematical forms (e.g. equations, graphics, diagrams, tables, words)
Representation Convert relevant information into various mathematical forms (e.g. equations, graphics, diagrams, tables, words)
Application/analysis Make judgments and draw appropriate conclusions based on the quantitative analysis of data, while recognizing the limits of this analysis
Assumptions Make and evaluate important assumptions in estimation, modeling, and data analysis
Communication Expressing quantitative evidence in support of the argument or purpose of the work (in terms of what evidence is used and how it is formatted, presented, and contextualized)

Each of the skills can be graded based on the following four benchmarks:

Level of achievement Definition
Benchmark Attempts to explain information presented in mathematical forms, but draws incorrect conclusions about what the information means
Milestone Provides somewhat accurate explanations of information presented in mathematical forms, but occasionally makes minor errors related to computations or units
Provides accurate explanations of information presented in mathematical forms
Capstone Provides accurate explanations of information presented in mathematical forms. Makes appropriate inferences based on that information

Evaluators are encouraged to assign a zero to any work sample or collection of works that does not meet benchmark level performance.

QR Workshops and events

Useful Links
  • Teaching resources
  • Internet resources for data analysis
  • Internet exercises and modules
  • Other QR projects across the world
Events Calendar